Chapter 5. Using AMQ Streams Operators
Use the AMQ Streams operators to manage your Kafka cluster, and Kafka topics and users.
5.1. Using the Cluster Operator
The Cluster Operator is used to deploy a Kafka cluster and other Kafka components.
The Cluster Operator is deployed using YAML installation files.
On OpenShift, a Kafka Connect deployment can incorporate a Source2Image feature to provide a convenient way to add additional connectors.
Additional resources
- Deploying the Cluster Operator in the Deploying and Upgrading AMQ Streams on OpenShift guide.
- Kafka Cluster configuration.
5.1.1. Cluster Operator configuration
You can configure the Cluster Operator using supported environment variables, and through its logging configuration.
The environment variables relate to container configuration for the deployment of the Cluster Operator image. For more information on image
configuration, see, Section 13.1.6, “image
”.
STRIMZI_NAMESPACE
A comma-separated list of namespaces that the operator should operate in. When not set, set to empty string, or set to
*
, the Cluster Operator will operate in all namespaces. The Cluster Operator deployment might use the OpenShift Downward API to set this automatically to the namespace the Cluster Operator is deployed in.Example configuration for Cluster Operator namespaces
env: - name: STRIMZI_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace
-
STRIMZI_FULL_RECONCILIATION_INTERVAL_MS
- Optional, default is 120000 ms. The interval between periodic reconciliations, in milliseconds.
STRIMZI_OPERATION_TIMEOUT_MS
- Optional, default 300000 ms. The timeout for internal operations, in milliseconds. This value should be increased when using AMQ Streams on clusters where regular OpenShift operations take longer than usual (because of slow downloading of Docker images, for example).
STRIMZI_OPERATOR_NAMESPACE
The name of the namespace where the AMQ Streams Cluster Operator is running. Do not configure this variable manually. Use the OpenShift Downward API.
env: - name: STRIMZI_OPERATOR_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace
STRIMZI_OPERATOR_NAMESPACE_LABELS
Optional. The labels of the namespace where the AMQ Streams Cluster Operator is running. Namespace labels are used to configure the namespace selector in network policies to allow the AMQ Streams Cluster Operator to only have access to the operands from the namespace with these labels. When not set, the namespace selector in network policies is configured to allow access to the AMQ Streams Cluster Operator from any namespace in the OpenShift cluster.
env: - name: STRIMZI_OPERATOR_NAMESPACE_LABELS value: label1=value1,label2=value2
STRIMZI_CUSTOM_RESOURCE_SELECTOR
Optional. Specifies label selector used to filter the custom resources handled by the operator. The operator will operate only on those custom resources which will have the specified labels set. Resources without these labels will not be seen by the operator. The label selector applies to
Kafka
,KafkaConnect
,KafkaConnectS2I
,KafkaBridge
,KafkaMirrorMaker
, andKafkaMirrorMaker2
resources.KafkaRebalance
andKafkaConnector
resources will be operated only when their corresponding Kafka and Kafka Connect clusters have the matching labels.env: - name: STRIMZI_CUSTOM_RESOURCE_SELECTOR value: label1=value1,label2=value2
STRIMZI_KAFKA_IMAGES
-
Required. This provides a mapping from Kafka version to the corresponding Docker image containing a Kafka broker of that version. The required syntax is whitespace or comma separated
<version>=<image>
pairs. For example2.6.0=registry.redhat.io/amq7/amq-streams-kafka-26-rhel7:1.7.0, 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel7:1.7.0
. This is used when aKafka.spec.kafka.version
property is specified but not theKafka.spec.kafka.image
in theKafka
resource. STRIMZI_DEFAULT_KAFKA_INIT_IMAGE
-
Optional, default
registry.redhat.io/amq7/amq-streams-rhel7-operator:1.7.0
. The image name to use as default for the init container started before the broker for initial configuration work (that is, rack support), if no image is specified as thekafka-init-image
in theKafka
resource. STRIMZI_KAFKA_CONNECT_IMAGES
-
Required. This provides a mapping from the Kafka version to the corresponding Docker image containing a Kafka connect of that version. The required syntax is whitespace or comma separated
<version>=<image>
pairs. For example2.6.0=registry.redhat.io/amq7/amq-streams-kafka-26-rhel7:1.7.0, 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel7:1.7.0
. This is used when aKafkaConnect.spec.version
property is specified but not theKafkaConnect.spec.image
. STRIMZI_KAFKA_CONNECT_S2I_IMAGES
-
Required. This provides a mapping from the Kafka version to the corresponding Docker image containing a Kafka connect of that version. The required syntax is whitespace or comma separated
<version>=<image>
pairs. For example2.6.0=registry.redhat.io/amq7/amq-streams-kafka-26-rhel7:1.7.0, 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel7:1.7.0
. This is used when aKafkaConnectS2I.spec.version
property is specified but not theKafkaConnectS2I.spec.image
. STRIMZI_KAFKA_MIRROR_MAKER_IMAGES
-
Required. This provides a mapping from the Kafka version to the corresponding Docker image containing a Kafka mirror maker of that version. The required syntax is whitespace or comma separated
<version>=<image>
pairs. For example2.6.0=registry.redhat.io/amq7/amq-streams-kafka-26-rhel7:1.7.0, 2.7.0=registry.redhat.io/amq7/amq-streams-kafka-27-rhel7:1.7.0
. This is used when aKafkaMirrorMaker.spec.version
property is specified but not theKafkaMirrorMaker.spec.image
. STRIMZI_DEFAULT_TOPIC_OPERATOR_IMAGE
-
Optional, default
registry.redhat.io/amq7/amq-streams-rhel7-operator:1.7.0
. The image name to use as the default when deploying the topic operator, if no image is specified as theKafka.spec.entityOperator.topicOperator.image
inKafka
resource. STRIMZI_DEFAULT_USER_OPERATOR_IMAGE
-
Optional, default
registry.redhat.io/amq7/amq-streams-rhel7-operator:1.7.0
. The image name to use as the default when deploying the user operator, if no image is specified as theKafka.spec.entityOperator.userOperator.image
in theKafka
resource. STRIMZI_DEFAULT_TLS_SIDECAR_ENTITY_OPERATOR_IMAGE
-
Optional, default
registry.redhat.io/amq7/amq-streams-kafka-27-rhel7:1.7.0
. The image name to use as the default when deploying the sidecar container which provides TLS support for the Entity Operator, if no image is specified as theKafka.spec.entityOperator.tlsSidecar.image
in theKafka
resource. STRIMZI_IMAGE_PULL_POLICY
-
Optional. The
ImagePullPolicy
which will be applied to containers in all pods managed by AMQ Streams Cluster Operator. The valid values areAlways
,IfNotPresent
, andNever
. If not specified, the OpenShift defaults will be used. Changing the policy will result in a rolling update of all your Kafka, Kafka Connect, and Kafka MirrorMaker clusters. STRIMZI_IMAGE_PULL_SECRETS
-
Optional. A comma-separated list of
Secret
names. The secrets referenced here contain the credentials to the container registries where the container images are pulled from. The secrets are used in theimagePullSecrets
field for allPods
created by the Cluster Operator. Changing this list results in a rolling update of all your Kafka, Kafka Connect, and Kafka MirrorMaker clusters. STRIMZI_KUBERNETES_VERSION
Optional. Overrides the Kubernetes version information detected from the API server.
Example configuration for Kubernetes version override
env: - name: STRIMZI_KUBERNETES_VERSION value: | major=1 minor=16 gitVersion=v1.16.2 gitCommit=c97fe5036ef3df2967d086711e6c0c405941e14b gitTreeState=clean buildDate=2019-10-15T19:09:08Z goVersion=go1.12.10 compiler=gc platform=linux/amd64
KUBERNETES_SERVICE_DNS_DOMAIN
Optional. Overrides the default OpenShift DNS domain name suffix.
By default, services assigned in the OpenShift cluster have a DNS domain name that uses the default suffix
cluster.local
.For example, for broker kafka-0:
<cluster-name>-kafka-0.<cluster-name>-kafka-brokers.<namespace>.svc.cluster.local
The DNS domain name is added to the Kafka broker certificates used for hostname verification.
If you are using a different DNS domain name suffix in your cluster, change the
KUBERNETES_SERVICE_DNS_DOMAIN
environment variable from the default to the one you are using in order to establish a connection with the Kafka brokers.STRIMZI_CONNECT_BUILD_TIMEOUT_MS
- Optional, default 300000 ms. The timeout for building new Kafka Connect images with additional connectots, in milliseconds. This value should be increased when using AMQ Streams to build container images containing many connectors or using a slow container registry.
5.1.1.1. Logging configuration by ConfigMap
The Cluster Operator’s logging is configured by the strimzi-cluster-operator
ConfigMap
.
A ConfigMap
containing logging configuration is created when installing the Cluster Operator. This ConfigMap
is described in the file install/cluster-operator/050-ConfigMap-strimzi-cluster-operator.yaml
. You configure Cluster Operator logging by changing the data field log4j2.properties
in this ConfigMap
.
To update the logging configuration, you can edit the 050-ConfigMap-strimzi-cluster-operator.yaml
file and then run the following command:
oc create -f install/cluster-operator/050-ConfigMap-strimzi-cluster-operator.yaml
Alternatively, edit the ConfigMap
directly:
oc edit cm strimzi-cluster-operator
To change the frequency of the reload interval, set a time in seconds in the monitorInterval
option in the created ConfigMap
.
If the ConfigMap
is missing when the Cluster Operator is deployed, the default logging values are used.
If the ConfigMap
is accidentally deleted after the Cluster Operator is deployed, the most recently loaded logging configuration is used. Create a new ConfigMap
to load a new logging configuration.
Do not remove the monitorInterval
option from the ConfigMap.
5.1.1.2. Restricting Cluster Operator access with network policy
The Cluster Operator can run in the same namespace as the resources it manages, or in a separate namespace. By default, the STRIMZI_OPERATOR_NAMESPACE
environment variable is configured to use the OpenShift Downward API to find which namespace the Cluster Operator is running in. If the Cluster Operator is running in the same namespace as the resources, only local access is required, and allowed by AMQ Streams.
If the Cluster Operator is running in a separate namespace to the resources it manages, any namespace in the OpenShift cluster is allowed access to the Cluster Operator unless network policy is configured. Use the optional STRIMZI_OPERATOR_NAMESPACE_LABELS
environment variable to establish network policy for the Cluster Operator using namespace labels. By adding namespace labels, access to the Cluster Operator is restricted to the namespaces specified.
Network policy configured for the Cluster Operator deployment
#... env: # ... - name: STRIMZI_OPERATOR_NAMESPACE_LABELS value: label1=value1,label2=value2 #...
5.1.1.3. Periodic reconciliation
Although the Cluster Operator reacts to all notifications about the desired cluster resources received from the OpenShift cluster, if the operator is not running, or if a notification is not received for any reason, the desired resources will get out of sync with the state of the running OpenShift cluster.
In order to handle failovers properly, a periodic reconciliation process is executed by the Cluster Operator so that it can compare the state of the desired resources with the current cluster deployments in order to have a consistent state across all of them. You can set the time interval for the periodic reconciliations using the [STRIMZI_FULL_RECONCILIATION_INTERVAL_MS] variable.
5.1.2. Provisioning Role-Based Access Control (RBAC)
For the Cluster Operator to function it needs permission within the OpenShift cluster to interact with resources such as Kafka
, KafkaConnect
, and so on, as well as the managed resources, such as ConfigMaps
, Pods
, Deployments
, StatefulSets
and Services
. Such permission is described in terms of OpenShift role-based access control (RBAC) resources:
-
ServiceAccount
, -
Role
andClusterRole
, -
RoleBinding
andClusterRoleBinding
.
In addition to running under its own ServiceAccount
with a ClusterRoleBinding
, the Cluster Operator manages some RBAC resources for the components that need access to OpenShift resources.
OpenShift also includes privilege escalation protections that prevent components operating under one ServiceAccount
from granting other ServiceAccounts
privileges that the granting ServiceAccount
does not have. Because the Cluster Operator must be able to create the ClusterRoleBindings
, and RoleBindings
needed by resources it manages, the Cluster Operator must also have those same privileges.
5.1.2.1. Delegated privileges
When the Cluster Operator deploys resources for a desired Kafka
resource it also creates ServiceAccounts
, RoleBindings
, and ClusterRoleBindings
, as follows:
The Kafka broker pods use a
ServiceAccount
calledcluster-name-kafka
-
When the rack feature is used, the
strimzi-cluster-name-kafka-init
ClusterRoleBinding
is used to grant thisServiceAccount
access to the nodes within the cluster via aClusterRole
calledstrimzi-kafka-broker
- When the rack feature is not used no binding is created
-
When the rack feature is used, the
-
The ZooKeeper pods use a
ServiceAccount
calledcluster-name-zookeeper
The Entity Operator pod uses a
ServiceAccount
calledcluster-name-entity-operator
-
The Topic Operator produces OpenShift events with status information, so the
ServiceAccount
is bound to aClusterRole
calledstrimzi-entity-operator
which grants this access via thestrimzi-entity-operator
RoleBinding
-
The Topic Operator produces OpenShift events with status information, so the
-
The pods for
KafkaConnect
andKafkaConnectS2I
resources use aServiceAccount
calledcluster-name-cluster-connect
-
The pods for
KafkaMirrorMaker
use aServiceAccount
calledcluster-name-mirror-maker
-
The pods for
KafkaMirrorMaker2
use aServiceAccount
calledcluster-name-mirrormaker2
-
The pods for
KafkaBridge
use aServiceAccount
calledcluster-name-bridge
5.1.2.2. ServiceAccount
The Cluster Operator is best run using a ServiceAccount
:
Example ServiceAccount
for the Cluster Operator
apiVersion: v1 kind: ServiceAccount metadata: name: strimzi-cluster-operator labels: app: strimzi
The Deployment
of the operator then needs to specify this in its spec.template.spec.serviceAccountName
:
Partial example of Deployment
for the Cluster Operator
apiVersion: apps/v1 kind: Deployment metadata: name: strimzi-cluster-operator labels: app: strimzi spec: replicas: 1 selector: matchLabels: name: strimzi-cluster-operator strimzi.io/kind: cluster-operator template: # ...
Note line 12, where the strimzi-cluster-operator
ServiceAccount
is specified as the serviceAccountName
.
5.1.2.3. ClusterRoles
The Cluster Operator needs to operate using ClusterRoles
that gives access to the necessary resources. Depending on the OpenShift cluster setup, a cluster administrator might be needed to create the ClusterRoles
.
Cluster administrator rights are only needed for the creation of the ClusterRoles
. The Cluster Operator will not run under the cluster admin account.
The ClusterRoles
follow the principle of least privilege and contain only those privileges needed by the Cluster Operator to operate Kafka, Kafka Connect, and ZooKeeper clusters. The first set of assigned privileges allow the Cluster Operator to manage OpenShift resources such as StatefulSets
, Deployments
, Pods
, and ConfigMaps
.
Cluster Operator uses ClusterRoles to grant permission at the namespace-scoped resources level and cluster-scoped resources level:
ClusterRole
with namespaced resources for the Cluster Operator
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: strimzi-cluster-operator-namespaced labels: app: strimzi rules: - apiGroups: - "rbac.authorization.k8s.io" resources: # The cluster operator needs to access and manage rolebindings to grant Strimzi components cluster permissions - rolebindings verbs: - get - list - watch - create - delete - patch - update - apiGroups: - "rbac.authorization.k8s.io" resources: # The cluster operator needs to access and manage roles to grant the entity operator permissions - roles verbs: - get - list - watch - create - delete - patch - update - apiGroups: - "" resources: # The cluster operator needs to access and delete pods, this is to allow it to monitor pod health and coordinate rolling updates - pods # The cluster operator needs to access and manage service accounts to grant Strimzi components cluster permissions - serviceaccounts # The cluster operator needs to access and manage config maps for Strimzi components configuration - configmaps # The cluster operator needs to access and manage services and endpoints to expose Strimzi components to network traffic - services - endpoints # The cluster operator needs to access and manage secrets to handle credentials - secrets # The cluster operator needs to access and manage persistent volume claims to bind them to Strimzi components for persistent data - persistentvolumeclaims verbs: - get - list - watch - create - delete - patch - update - apiGroups: - "kafka.strimzi.io" resources: # The cluster operator runs the KafkaAssemblyOperator, which needs to access and manage Kafka resources - kafkas - kafkas/status # The cluster operator runs the KafkaConnectAssemblyOperator, which needs to access and manage KafkaConnect resources - kafkaconnects - kafkaconnects/status # The cluster operator runs the KafkaConnectS2IAssemblyOperator, which needs to access and manage KafkaConnectS2I resources - kafkaconnects2is - kafkaconnects2is/status # The cluster operator runs the KafkaConnectorAssemblyOperator, which needs to access and manage KafkaConnector resources - kafkaconnectors - kafkaconnectors/status # The cluster operator runs the KafkaMirrorMakerAssemblyOperator, which needs to access and manage KafkaMirrorMaker resources - kafkamirrormakers - kafkamirrormakers/status # The cluster operator runs the KafkaBridgeAssemblyOperator, which needs to access and manage BridgeMaker resources - kafkabridges - kafkabridges/status # The cluster operator runs the KafkaMirrorMaker2AssemblyOperator, which needs to access and manage KafkaMirrorMaker2 resources - kafkamirrormaker2s - kafkamirrormaker2s/status # The cluster operator runs the KafkaRebalanceAssemblyOperator, which needs to access and manage KafkaRebalance resources - kafkarebalances - kafkarebalances/status verbs: - get - list - watch - create - delete - patch - update - apiGroups: # The cluster operator needs the extensions api as the operator supports Kubernetes version 1.11+ # apps/v1 was introduced in Kubernetes 1.14 - "extensions" resources: # The cluster operator needs to access and manage deployments to run deployment based Strimzi components - deployments - deployments/scale # The cluster operator needs to access replica sets to manage Strimzi components and to determine error states - replicasets # The cluster operator needs to access and manage replication controllers to manage replicasets - replicationcontrollers # The cluster operator needs to access and manage network policies to lock down communication between Strimzi components - networkpolicies # The cluster operator needs to access and manage ingresses which allow external access to the services in a cluster - ingresses verbs: - get - list - watch - create - delete - patch - update - apiGroups: - "apps" resources: # The cluster operator needs to access and manage deployments to run deployment based Strimzi components - deployments - deployments/scale - deployments/status # The cluster operator needs to access and manage stateful sets to run stateful sets based Strimzi components - statefulsets # The cluster operator needs to access replica-sets to manage Strimzi components and to determine error states - replicasets verbs: - get - list - watch - create - delete - patch - update - apiGroups: - "" resources: # The cluster operator needs to be able to create events and delegate permissions to do so - events verbs: - create - apiGroups: # OpenShift S2I requirements - apps.openshift.io resources: - deploymentconfigs - deploymentconfigs/scale - deploymentconfigs/status - deploymentconfigs/finalizers verbs: - get - list - watch - create - delete - patch - update - apiGroups: # OpenShift S2I requirements - build.openshift.io resources: - buildconfigs - buildconfigs/instantiate - builds verbs: - get - list - watch - create - delete - patch - update - apiGroups: # OpenShift S2I requirements - image.openshift.io resources: - imagestreams - imagestreams/status verbs: - get - list - watch - create - delete - patch - update - apiGroups: - networking.k8s.io resources: # The cluster operator needs to access and manage network policies to lock down communication between Strimzi components - networkpolicies # The cluster operator needs to access and manage ingresses which allow external access to the services in a cluster - ingresses verbs: - get - list - watch - create - delete - patch - update - apiGroups: - route.openshift.io resources: # The cluster operator needs to access and manage routes to expose Strimzi components for external access - routes - routes/custom-host verbs: - get - list - watch - create - delete - patch - update - apiGroups: - policy resources: # The cluster operator needs to access and manage pod disruption budgets this limits the number of concurrent disruptions # that a Strimzi component experiences, allowing for higher availability - poddisruptionbudgets verbs: - get - list - watch - create - delete - patch - update
The second includes the permissions needed for cluster-scoped resources.
ClusterRole
with cluster-scoped resources for the Cluster Operator
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: strimzi-cluster-operator-global labels: app: strimzi rules: - apiGroups: - "rbac.authorization.k8s.io" resources: # The cluster operator needs to create and manage cluster role bindings in the case of an install where a user # has specified they want their cluster role bindings generated - clusterrolebindings verbs: - get - list - watch - create - delete - patch - update - apiGroups: - storage.k8s.io resources: # The cluster operator requires "get" permissions to view storage class details # This is because only a persistent volume of a supported storage class type can be resized - storageclasses verbs: - get - apiGroups: - "" resources: # The cluster operator requires "list" permissions to view all nodes in a cluster # The listing is used to determine the node addresses when NodePort access is configured # These addresses are then exposed in the custom resource states - nodes verbs: - list
The strimzi-kafka-broker
ClusterRole
represents the access needed by the init container in Kafka pods that is used for the rack feature. As described in the Delegated privileges section, this role is also needed by the Cluster Operator in order to be able to delegate this access.
ClusterRole
for the Cluster Operator allowing it to delegate access to OpenShift nodes to the Kafka broker pods
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: strimzi-kafka-broker labels: app: strimzi rules: - apiGroups: - "" resources: # The Kafka Brokers require "get" permissions to view the node they are on # This information is used to generate a Rack ID that is used for High Availability configurations - nodes verbs: - get
The strimzi-topic-operator
ClusterRole
represents the access needed by the Topic Operator. As described in the Delegated privileges section, this role is also needed by the Cluster Operator in order to be able to delegate this access.
ClusterRole
for the Cluster Operator allowing it to delegate access to events to the Topic Operator
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: strimzi-entity-operator labels: app: strimzi rules: - apiGroups: - "kafka.strimzi.io" resources: # The entity operator runs the KafkaTopic assembly operator, which needs to access and manage KafkaTopic resources - kafkatopics - kafkatopics/status # The entity operator runs the KafkaUser assembly operator, which needs to access and manage KafkaUser resources - kafkausers - kafkausers/status verbs: - get - list - watch - create - patch - update - delete - apiGroups: - "" resources: - events verbs: # The entity operator needs to be able to create events - create - apiGroups: - "" resources: # The entity operator user-operator needs to access and manage secrets to store generated credentials - secrets verbs: - get - list - watch - create - delete - patch - update
The strimzi-kafka-client
ClusterRole
represents the access needed by the components based on Kafka clients which use the client rack-awareness. As described in the Delegated privileges section, this role is also needed by the Cluster Operator in order to be able to delegate this access.
ClusterRole
for the Cluster Operator allowing it to delegate access to OpenShift nodes to the Kafka client based pods
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: strimzi-kafka-client labels: app: strimzi rules: - apiGroups: - "" resources: # The Kafka clients (Connect, Mirror Maker, etc.) require "get" permissions to view the node they are on # This information is used to generate a Rack ID (client.rack option) that is used for consuming from the closest # replicas when enabled - nodes verbs: - get
5.1.2.4. ClusterRoleBindings
The operator needs ClusterRoleBindings
and RoleBindings
which associates its ClusterRole
with its ServiceAccount
: ClusterRoleBindings
are needed for ClusterRoles
containing cluster-scoped resources.
Example ClusterRoleBinding
for the Cluster Operator
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: strimzi-cluster-operator labels: app: strimzi subjects: - kind: ServiceAccount name: strimzi-cluster-operator namespace: myproject roleRef: kind: ClusterRole name: strimzi-cluster-operator-global apiGroup: rbac.authorization.k8s.io
ClusterRoleBindings
are also needed for the ClusterRoles
needed for delegation:
Example ClusterRoleBinding
for the Cluster Operator for the Kafka broker rack-awarness
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: strimzi-cluster-operator-kafka-broker-delegation labels: app: strimzi # The Kafka broker cluster role must be bound to the cluster operator service account so that it can delegate the cluster role to the Kafka brokers. # This must be done to avoid escalating privileges which would be blocked by Kubernetes. subjects: - kind: ServiceAccount name: strimzi-cluster-operator namespace: myproject roleRef: kind: ClusterRole name: strimzi-kafka-broker apiGroup: rbac.authorization.k8s.io
and
Example ClusterRoleBinding
for the Cluster Operator for the Kafka client rack-awarness
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: strimzi-cluster-operator-kafka-client-delegation labels: app: strimzi # The Kafka clients cluster role must be bound to the cluster operator service account so that it can delegate the # cluster role to the Kafka clients using it for consuming from closest replica. # This must be done to avoid escalating privileges which would be blocked by Kubernetes. subjects: - kind: ServiceAccount name: strimzi-cluster-operator namespace: myproject roleRef: kind: ClusterRole name: strimzi-kafka-client apiGroup: rbac.authorization.k8s.io
ClusterRoles
containing only namespaced resources are bound using RoleBindings
only.
apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: strimzi-cluster-operator labels: app: strimzi subjects: - kind: ServiceAccount name: strimzi-cluster-operator namespace: myproject roleRef: kind: ClusterRole name: strimzi-cluster-operator-namespaced apiGroup: rbac.authorization.k8s.io
apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: strimzi-cluster-operator-entity-operator-delegation labels: app: strimzi # The Entity Operator cluster role must be bound to the cluster operator service account so that it can delegate the cluster role to the Entity Operator. # This must be done to avoid escalating privileges which would be blocked by Kubernetes. subjects: - kind: ServiceAccount name: strimzi-cluster-operator namespace: myproject roleRef: kind: ClusterRole name: strimzi-entity-operator apiGroup: rbac.authorization.k8s.io
5.2. Using the Topic Operator
When you create, modify or delete a topic using the KafkaTopic
resource, the Topic Operator ensures those changes are reflected in the Kafka cluster.
The Deploying and Upgrading AMQ Streams on OpenShift guide provides instructions to deploy the Topic Operator:
5.2.1. Kafka topic resource
The KafkaTopic
resource is used to configure topics, including the number of partitions and replicas.
The full schema for KafkaTopic
is described in KafkaTopic
schema reference.
5.2.1.1. Identifying a Kafka cluster for topic handling
A KafkaTopic
resource includes a label that defines the appropriate name of the Kafka cluster (derived from the name of the Kafka
resource) to which it belongs.
For example:
apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaTopic metadata: name: topic-name-1 labels: strimzi.io/cluster: my-cluster
The label is used by the Topic Operator to identify the KafkaTopic
resource and create a new topic, and also in subsequent handling of the topic.
If the label does not match the Kafka cluster, the Topic Operator cannot identify the KafkaTopic
and the topic is not created.
5.2.1.2. Kafka topic usage recommendations
When working with topics, be consistent. Always operate on either KafkaTopic
resources or topics directly in OpenShift. Avoid routinely switching between both methods for a given topic.
Use topic names that reflect the nature of the topic, and remember that names cannot be changed later.
If creating a topic in Kafka, use a name that is a valid OpenShift resource name, otherwise the Topic Operator will need to create the corresponding KafkaTopic
with a name that conforms to the OpenShift rules.
Recommendations for identifiers and names in OpenShift are outlined in Identifiers and Names in OpenShift community article.
5.2.1.3. Kafka topic naming conventions
Kafka and OpenShift impose their own validation rules for the naming of topics in Kafka and KafkaTopic.metadata.name
respectively. There are valid names for each which are invalid in the other.
Using the spec.topicName
property, it is possible to create a valid topic in Kafka with a name that would be invalid for the Kafka topic in OpenShift.
The spec.topicName
property inherits Kafka naming validation rules:
- The name must not be longer than 249 characters.
-
Valid characters for Kafka topics are ASCII alphanumerics,
.
,_
, and-
. -
The name cannot be
.
or..
, though.
can be used in a name, such asexampleTopic.
or.exampleTopic
.
spec.topicName
must not be changed.
For example:
apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
name: topic-name-1
spec:
topicName: topicName-1 1
# ...
- 1
- Upper case is invalid in OpenShift.
cannot be changed to:
apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaTopic metadata: name: topic-name-1 spec: topicName: name-2 # ...
Some Kafka client applications, such as Kafka Streams, can create topics in Kafka programmatically. If those topics have names that are invalid OpenShift resource names, the Topic Operator gives them a valid metadata.name
based on the Kafka name. Invalid characters are replaced and a hash is appended to the name. For example:
apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaTopic metadata: name: mytopic---c55e57fe2546a33f9e603caf57165db4072e827e spec: topicName: myTopic # ...
5.2.2. Topic Operator topic store
The Topic Operator uses Kafka to store topic metadata describing topic configuration as key-value pairs. The topic store is based on the Kafka Streams key-value mechanism, which uses Kafka topics to persist the state.
Topic metadata is cached in-memory and accessed locally within the Topic Operator. Updates from operations applied to the local in-memory cache are persisted to a backup topic store on disk. The topic store is continually synchronized with updates from Kafka topics or OpenShift KafkaTopic
custom resources. Operations are handled rapidly with the topic store set up this way, but should the in-memory cache crash it is automatically repopulated from the persistent storage.
5.2.2.1. Internal topic store topics
Internal topics support the handling of topic metadata in the topic store.
__strimzi_store_topic
- Input topic for storing the topic metadata
__strimzi-topic-operator-kstreams-topic-store-changelog
- Retains a log of compacted topic store values
Do not delete these topics, as they are essential to the running of the Topic Operator.
5.2.2.2. Migrating topic metadata from ZooKeeper
In previous releases of AMQ Streams, topic metadata was stored in ZooKeeper. The new process removes this requirement, bringing the metadata into the Kafka cluster, and under the control of the Topic Operator.
When upgrading to AMQ Streams 1.7, the transition to Topic Operator control of the topic store is seamless. Metadata is found and migrated from ZooKeeper, and the old store is deleted.
5.2.2.3. Downgrading to an AMQ Streams version that uses ZooKeeper to store topic metadata
If you are reverting back to a version of AMQ Streams earlier than 0.22, which uses ZooKeeper for the storage of topic metadata, you still downgrade your Cluster Operator to the previous version, then downgrade Kafka brokers and client applications to the previous Kafka version as standard.
However, you must also delete the topics that were created for the topic store using a kafka-admin
command, specifying the bootstrap address of the Kafka cluster. For example:
oc run kafka-admin -ti --image=registry.redhat.io/amq7/amq-streams-kafka-27-rhel7:1.7.0 --rm=true --restart=Never -- ./bin/kafka-topics.sh --bootstrap-server localhost:9092 --topic __strimzi-topic-operator-kstreams-topic-store-changelog --delete && ./bin/kafka-topics.sh --bootstrap-server localhost:9092 --topic __strimzi_store_topic --delete
The command must correspond to the type of listener and authentication used to access the Kafka cluster.
The Topic Operator will reconstruct the ZooKeeper topic metadata from the state of the topics in Kafka.
5.2.2.4. Topic Operator topic replication and scaling
The recommended configuration for topics managed by the Topic Operator is a topic replication factor of 3, and a minimum of 2 in-sync replicas.
apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaTopic metadata: name: my-topic labels: strimzi.io/cluster: my-cluster spec: partitions: 1 1 replicas: 3 2 config: min.insync.replicas=2 3 #...
- 1
- The number of partitions for the topic. Generally, 1 partition is sufficient.
- 2
- The number of replica topic partitions. Currently, this cannot be changed in the
KafkaTopic
resource, but it can be changed using thekafka-reassign-partitions.sh
tool. - 3
- The minimum number of replica partitions that a message must be successfully written to, or an exception is raised.
In-sync replicas are used in conjunction with the acks
configuration for producer applications. The acks
configuration determines the number of follower partitions a message must be replicated to before the message is acknowledged as successfully received. The Topic Operator runs with acks=all
, whereby messages must be acknowledged by all in-sync replicas.
When scaling Kafka clusters by adding or removing brokers, replication factor configuration is not changed and replicas are not reassigned automatically. However, you can use the kafka-reassign-partitions.sh
tool to change the replication factor, and manually reassign replicas to brokers.
Alternatively, though the integration of Cruise Control for AMQ Streams cannot change the replication factor for topics, the optimization proposals it generates for rebalancing Kafka include commands that transfer partition replicas and change partition leadership.
5.2.2.5. Handling changes to topics
A fundamental problem that the Topic Operator needs to solve is that there is no single source of truth: both the KafkaTopic
resource and the Kafka topic can be modified independently of the Topic Operator. Complicating this, the Topic Operator might not always be able to observe changes at each end in real time. For example, when the Topic Operator is down.
To resolve this, the Topic Operator maintains information about each topic in the topic store. When a change happens in the Kafka cluster or OpenShift, it looks at both the state of the other system and the topic store in order to determine what needs to change to keep everything in sync. The same thing happens whenever the Topic Operator starts, and periodically while it is running.
For example, suppose the Topic Operator is not running, and a KafkaTopic
called my-topic is created. When the Topic Operator starts, the topic store does not contain information on my-topic, so it can infer that the KafkaTopic
was created after it was last running. The Topic Operator creates the topic corresponding to my-topic, and also stores metadata for my-topic in the topic store.
If you update Kafka topic configuration or apply a change through the KafkaTopic
custom resource, the topic store is updated after the Kafka cluster is reconciled.
The topic store also allows the Topic Operator to manage scenarios where the topic configuration is changed in Kafka topics and updated through OpenShift KafkaTopic
custom resources, as long as the changes are not incompatible. For example, it is possible to make changes to the same topic config key, but to different values. For incompatible changes, the Kafka configuration takes priority, and the KafkaTopic
is updated accordingly.
You can also use the KafkaTopic
resource to delete topics using a oc delete -f KAFKA-TOPIC-CONFIG-FILE
command. To be able to do this, delete.topic.enable
must be set to true
(default) in the spec.kafka.config
of the Kafka resource.
5.2.3. Configuring a Kafka topic
Use the properties of the KafkaTopic
resource to configure a Kafka topic.
You can use oc apply
to create or modify topics, and oc delete
to delete existing topics.
For example:
-
oc apply -f <topic-config-file>
-
oc delete KafkaTopic <topic-name>
This procedure shows how to create a topic with 10 partitions and 2 replicas.
Before you start
It is important that you consider the following before making your changes:
Kafka does not support making the following changes through the
KafkaTopic
resource:-
Changing topic names using
spec.topicName
-
Decreasing partition size using
spec.partitions
-
Changing topic names using
-
You cannot use
spec.replicas
to change the number of replicas that were initially specified. -
Increasing
spec.partitions
for topics with keys will change how records are partitioned, which can be particularly problematic when the topic uses semantic partitioning.
Prerequisites
- A running Kafka cluster configured with a Kafka broker listener using TLS authentication and encryption.
- A running Topic Operator (typically deployed with the Entity Operator).
-
For deleting a topic,
delete.topic.enable=true
(default) in thespec.kafka.config
of theKafka
resource.
Procedure
Prepare a file containing the
KafkaTopic
to be created.An example
KafkaTopic
apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaTopic metadata: name: orders labels: strimzi.io/cluster: my-cluster spec: partitions: 10 replicas: 2
TipWhen modifying a topic, you can get the current version of the resource using
oc get kafkatopic orders -o yaml
.Create the
KafkaTopic
resource in OpenShift.oc apply -f TOPIC-CONFIG-FILE
5.2.4. Configuring the Topic Operator with resource requests and limits
You can allocate resources, such as CPU and memory, to the Topic Operator and set a limit on the amount of resources it can consume.
Prerequisites
- The Cluster Operator is running.
Procedure
Update the Kafka cluster configuration in an editor, as required:
oc edit kafka MY-CLUSTER
In the
spec.entityOperator.topicOperator.resources
property in theKafka
resource, set the resource requests and limits for the Topic Operator.apiVersion: kafka.strimzi.io/v1beta2 kind: Kafka spec: # Kafka and ZooKeeper sections... entityOperator: topicOperator: resources: requests: cpu: "1" memory: 500Mi limits: cpu: "1" memory: 500Mi
Apply the new configuration to create or update the resource.
oc apply -f KAFKA-CONFIG-FILE
5.3. Using the User Operator
When you create, modify or delete a user using the KafkaUser
resource, the User Operator ensures those changes are reflected in the Kafka cluster.
The Deploying and Upgrading AMQ Streams on OpenShift guide provides instructions to deploy the User Operator:
For more information about the schema, see KafkaUser
schema reference.
Authenticating and authorizing access to Kafka
Use KafkaUser
to enable the authentication and authorization mechanisms that a specific client uses to access Kafka.
For more information on using KafkUser
to manage users and secure access to Kafka brokers, see Securing access to Kafka brokers.
5.3.1. Configuring the User Operator with resource requests and limits
You can allocate resources, such as CPU and memory, to the User Operator and set a limit on the amount of resources it can consume.
Prerequisites
- The Cluster Operator is running.
Procedure
Update the Kafka cluster configuration in an editor, as required:
oc edit kafka MY-CLUSTER
In the
spec.entityOperator.userOperator.resources
property in theKafka
resource, set the resource requests and limits for the User Operator.apiVersion: kafka.strimzi.io/v1beta2 kind: Kafka spec: # Kafka and ZooKeeper sections... entityOperator: userOperator: resources: requests: cpu: "1" memory: 500Mi limits: cpu: "1" memory: 500Mi
Save the file and exit the editor. The Cluster Operator applies the changes automatically.
5.4. Monitoring operators using Prometheus metrics
AMQ Streams operators expose Prometheus metrics. The metrics are automatically enabled and contain information about:
- Number of reconciliations
- Number of Custom Resources the operator is processing
- Duration of reconciliations
- JVM metrics from the operators
Additionally, we provide example Grafana dashboards.
For more information, see Setting up metrics and dashboards for AMQ Streams in the Deploying and upgrading AMQ Streams on OpenShift guide.